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UI for the summary table module

Usage

summary_table_ui(
  module_id,
  show_pop_flag_selection = FALSE,
  show_aggregate_method = FALSE,
  default_pop_flags_after_groups = FALSE,
  default_total = TRUE,
  default_drop_na = FALSE,
  default_drop_empty_rows = FALSE,
  default_drop_empty_cols = FALSE,
  default_show_category_n = TRUE,
  default_denom = "N",
  default_stats = NULL,
  choices_stats = NULL,
  default_aggregate_method = NULL,
  choices_aggregate_method = NULL
)

Arguments

module_id

[character(1)]

A string that serves as a unique identifier for the module.

show_pop_flag_selection

[logical(1)]

A flag to indicate whether to show the population flag selection. Other associated arguments are default_pop_flags and choices_pop_flags.

show_aggregate_method

[logical(1)]

A flag to indicate whether to show (and apply) aggregate methods. If more than one row per participant exists after population grouping and row categorization has been applied then aggreation of those rows can be applied using a selected method. Other associated arguments are default_aggregate_method and choices_aggregate_method.

default_pop_flags_after_groups

[logical(1)]

A flag specifying the default value for the checkbox that determines whether to show the population flags after the group variables.

default_total

[logical(1)]

A flag specifying the default value for the checkbox that determines whether to add a total group column.

default_drop_na

[logical(1)]

A flag specifying the default value for the checkbox that determines whether to drop NA values from selected 'group by' and 'row by' variables.

default_drop_empty_rows

[logical(1)]

A flag specifying the default value for the checkbox that determines whether to remove rows with no data from the analysis results.

default_drop_empty_cols

[logical(1)]

A flag specifying the default value for the checkbox that determines whether to remove cols with no participant data.

default_show_category_n

[logical(1)]

A flag specifying the default value for the checkbox that determines whether to show the 'n' category when summarizing categorical data.

default_denom

["N" | "n"]

A string, either "N" or "n", indicating the default of whether the denominator for categorical data should be taken as the number of participants from the population grouping ("N") or the number of participants from the 'row by' grouping for each population grouping ("n"). If the user selects to drop NA values then those values will be excluded from determining the "n" denominator.

default_stats

[character(1+) | NULL]

A vector of strings from the names of the list elements in stats_formats or stats_functions, used as the default selection of statistics for summarizing numerical data.

choices_stats

[character(1+) | NULL]

A vector of strings from the names of the list elements from summary_table_server() arguments, stats_formats and stats_functions, used as the choice of statistics for summarizing numerical data.

default_aggregate_method

[character(1) | NULL]

A string indicating the function name defined in choices_aggregate_method to use as the default for aggregating rows when show_aggregate_method = TRUE. The function is applied to the analysis variable when more than one row per participant exists after population grouping and row categorization has been applied. The double colon (::) namespace resolution operator can be used to specify a function from a specific package, e.g., "dplyr::first".

choices_aggregate_method

[character(1+) | NULL]

A vector of named strings indicating the functions that can be used for aggregating rows when show_aggregate_method = TRUE. The functions apply to the analysis variable when more than one row per participant exists after population grouping and row categorization has been applied. The double colon (::) namespace resolution operator can be used to specify functions from specific packages, e.g., "dplyr::first". The names associated to the vector elements are displayed in the UI radio button selections.

Value

A shiny::tagList containing the user interface for selecting hierarchy, group, and minimum percentage for event counting.